Health Disparities Due to Diminished Return Among Black Americans: Public Policy Solutions

Health Disparities Due to Diminished Return among Black Americans: Public Policy Solutions

Shervin Assari MD MPH 1,2,3

1) Center for Research on Ethnicity, Culture, and Health (CRECH), School of Public Health, University

of Michigan, Ann Arbor, MI, USA

2) Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA

3) Institute for Healthcare Policy and Innovation (IHPI), University of Michigan, Ann Arbor, MI, USA

Email: [email protected]

4250 Plymouth Rd. Ann Arbor, MI 48109-2700

Funding

Shervin Assari is supported by the Heinz C. Prechter Bipolar Research Fund and the Richard Tam

Foundation at the University of Michigan Depression Center.

This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/sipr.12042.

Acknowledgment

Author wishes to thank Stephanie Vidaillet Gelderloos, Brianna Preiser, and Maeva Adoumie to their contribution to the drafts of this paper.

Abstract:

There are persistent and pervasive disparities in the health of Black people compared to non-

Hispanic Whites in the United States. There are many reasons for this gap; this paper explores the role of “Blacks’ diminished gain” as a mechanism behind racial health disparities. Diminished gain is a phenomenon wherein the health effects of certain socio-economic resources and psychological assets are systematically smaller for Blacks compared to Whites. These patterns are robust, with similar findings across different resources, assets, outcomes, settings, cohorts, and age groups.

However, the role of diminished gain as a main contributing mechanism to racial health disparities has been historically overlooked. This article reviews the research literature on diminished gain and discusses possible causes for it, such as the societal barriers created by structural racism. Policy solutions that may reduce Blacks’ diminished gain are discussed.

Keywords: Social and Economic Inequalities, Racial and Ethnic Health Disparities, Socioeconomic

Status, Structural Barriers, Racism, Social Policy, Public Policy

Introduction

Across almost all domains, people who self-identify as Black or African American experience worse health compared to people who self-identify as White (Williams & Collins, 1995, Williams, Priest, &

Anderson, 2016). Racial health disparities start even before birth (Lu & Halfon, 2003) and extend throughout childhood (Caprio, et al., 2008), adulthood (McClellan, et al., 2006) and older adulthood

(Pappas, Queen, Hadden, & Fisher, 1993). Some well-documented examples are greater infant mortality rate (MacDorman, 2011), greater incidence of childhood chronic disease (Miller, 2000) and higher mortality and morbidity of Blacks later in life (McClellan, et al., 2006; Murray, et al., 2006).

Although the overall health of all Americans has improved over the past several decades, the racial health gap has remained relatively constant (National Center for Health Statistics. 2015). In the past, economic, social, and health policies and programs that have addressed these health disparities have been largely unsuccessful in narrowing the disparities in morbidity and mortality between Black and White Americans (Griffith, Evans, & Bor, 2017; Artiga, Damico, & Garfield, 2015). (Similar health disparities impact other minority groups including Hispanics and Native Americans but for reasons of length will not be discussed in this article)

There are multiple interactive reasons for the continued health gap between Black minority group member minorities and White majority group members, and no single model or cause can fully explain the complex bio-social mechanisms. Of course, the possibility exists that there are population-level genetic differences that result in differential incidence rates for some diseases, as well as differences in the way certain diseases develop and progress. Such differences as causes of health disparities merit examination, but it is highly doubtful that they can fully explain the racial/ethnic differences in health status. Other likely causes of health status disparities concern

inequities in the quality of healthcare received by different social groups (Nelson, Stith, & Smedley,

2002) as well as cultural differences of patients receiving healthcare (Caprio, et al., 2008). This paper almost exclusively focuses on racial health disparities due to the structural racism embedded in the

U.S. social structure, meaning the system of socioeconomic stratification (e.g., the class structure), social institutions, or other patterned relations between large social groups (Krieger, 2012; Williams

& Mohammed, 2013). The core thesis is that due to American social structure, economic resources

(i.e. material and symbolic goods, which can be accessed and used in social actions) and psychological assets (i.e., personal attributes and traits such as optimism, coping, and mood) systemically generate larger health gains for White Americans than they do Black Americans.

This paper reviews research literature showing that first health is largely shaped by societal factors outside the health sector, and, second, social resources and psychological assets are essential for health (Link & Phelan, 1995). The next section summarizes research that shows Blacks experience diminished gains from certain socioeconomic resources and psychological assets. After discussion of the meaning of these findings, we propose five potential mechanisms that may explain such differential effects. Implications for theory, research, and policy are then addressed.

The primary sources for the data presented in this article are secondary analyses conducted by the author’s research team. These studies are based on the following five national surveys or cohorts: 1) the Americans’ Changing Lives (ACL) study, a 25-year cohort of 3600+ adults (1986-2011),

2) the Midlife in the United States (MIDUS) study, a 10-year cohort of 7100+ adults (1995-2004), 3) the Religion, Aging, and Health Survey (RAHS), a 3-year cohort of 1500 older adults (2001-2004), 4)

Health and Retirement Study (HRS), an ongoing cohort of 37000+ older adults (1992-current), and 5) the National Survey of American Life (NSAL), a survey of 6000+ adults and 1100+ adolescents (2001-

2003). These studies have mostly recruited representative samples of children, adolescents, and adults living in the United States. As a result, the results are generalizable to the U.S. population.

Although these studies have included several different racial/ethnic groups, most of these findings are relevant to health gaps between Black and Whites, as they are typically the largest and most extensively studied.

Economic and Social Resources, Personal Assets, and Health

The World Health Organization (WHO) Commission on Social Determinants of Health (2008) and many public health researchers (e.g., Marmot, Allen, Bell, & Goldblatt, 2012) have argued that people’s health and illness are initially shaped by factors outside the health sector. That is, exposure to enduring social ills such as poverty, poor education, and unemployment are strong contributors to racial health disparities. Thus, many health problems have origins that may predate exposure to disparities in the quality of the healthcare Black patients receive. This view does not challenge the importance of healthcare disparities in health status disparity (Nelson, Stith, & Smedley, 2002) but instead argues that such disparities do not fully explain the large gaps in the health of Blacks and

Whites.

Differential Effects versus Differential Exposures

Our model of health disparities argues that there are two related but distinct processes that cause the Black-White health gap in United States. The first is “differential exposure,” in which

Blacks are less likely to have access to certain resources (e.g. quality education, well-paying employment) and more likely to be exposed to certain risk factors (e.g. discrimination). The second process is “diminished gain” or “differential effects,” in which Blacks are less likely to experience benefits, or positive consequences, from resources in their environment they do receive and assets

they do possess. Both “differential exposure” and “differential effects” contribute to the development of racial health disparities across the life course.

Economic and social resources are essential for maintaining health and avoiding illness (Link

& Phelan, 1995). Mirowsky and Ross (2003) have described the health effects of socioeconomic resources, such as education, as enduring, consistent, and growing. Social determinants of health

(SDH; i.e. the conditions in which people are born, grow, live, work, and age) and SES (i.e. individual's or family's economic and social position in relation to others, based on income, education, and occupation) provide access to material and human resources. These resources collectively minimize the risk of exposure to, and subsequent negative consequences of, illness (Phelan, Link, &

Tehranifar, 2010). Multiple cross sectional and longitudinal studies of the factors that affect people’s health (e.g., Health and Retirement Study (HRS) (Bowen & González, 2010), the Panel Study of

Income Dynamics (McDonough, Williams, House, & Duncan,1999), the Survey of Health, Aging and

Retirement in Europe (SHARE) (Leopold & Engelhardt, 2013), and the Americans’ Changing Lives

(ACL) Study (Herd, Goesling, & House, 2007), find that education, employment, and income are among the most important social resources that reduce risk of premature morbidity (Gueorguieva, et al., 2009) and mortality (Hummer & Hernandez, 2013).

However, Everson-Rose and Lewis (2004) assert that, at least some of the health effects of economic and social resources and SDH are mitigated by certain psychological or personal assets or resources. For example, mastery, sense of agency, and self-efficacy (i.e. beliefs about one’s ability to meaningfully affect one’s environment) all mediate the effects of economic adversities on physical and mental health outcomes (Everson-Rose, House, Mero 2004). Subsequent research by Surtees et

al. (2010) and Turiano, et al. (2014) have further supported the importance of personal assets in the maintenance of individuals’ health.

One of the primary foci of the recent research by our team has been to use national data sets to determine the relative impact of exposure to social, economic, and psychological resources and the mitigating effects of certain personal assets or strengths on the health of Blacks and Whites.

Table 1 summarizes the results of more than twenty papers by my colleagues and I documenting the differential effects of social resources and psychological assets on health of Whites and Blacks. As previously suggested, these studies have consistently found smaller health benefits from access to social resources and possession of certain assets for Blacks compared to Whites. These findings seem to hold across developmental phases, as they are observed among young people (Assari,

Thomas, Caldwell, & Mincy, 2017), adults (Assari & Lankarani, 2016a) and older adults (Assari &

Lankarani, 2016b).

For example, a 25-year follow up of more than 3000 adults shows that educational attainment (Assari & Lankarani, 2016a) and employment (Assari, 2017a) have stronger protective effects on the life expectancy of Whites compared to Blacks. In another study, we found that having access to a higher number of social contacts (i.e. being a member of a larger social network) increased life expectancy of Whites but not Blacks in a sample over 25 years of age (Assari, 2017b).

Similarly, higher levels of self-efficacy (Assari, 2017c) and sense of control over life (Assari, 2017d) may better reduce the risk of premature mortality for Whites than for Blacks over time. Holmes and

Zajacova (2014) report similar findings.

Thus, not all racial/ethnic health disparities are simply due to lower SES (LaVeist, 2005), higher stress (Lantz, House, Mero, & Williams, 2005), higher levels of discrimination (Williams,

Neighbors, & Jackson 2003), and the inferior healthcare (Nelson, Stith, & Smedley, 2002) that Blacks and other minority groups are disproportionately exposed to. It is also the relative gain or loss of such factors that affects a person’s health.

These findings suggest that there are multiple related causes of health disparities. That is, some people have argued that it is one’s social class, rather than one’s race, that contributes to their health status. Such arguments ignore the strong covariation between race, social class, and where one lives in the US. (“place”). Thus, others have persuasively argued that it is both race and the risk factors that covary with race that are responsible for the poor health of Blacks relative to Whites

(Navaro, 1990). Some researchers (e.g., LaVeist 2005) have tried to disentangle the effects of race and place from SES, with the assumption that SES, place, and other risk factors (LaVeist, Pollack,

Thorpe, Fesahazion, Gaskin 2011) fully explain racial health disparities.

Probably the most important contribution of this paper is to present convincing evidence that suggests not all of the health disparities are due to the differential exposure of Blacks and

Whites to risk and protective factors. Instead, the same protective and risk factors result in various levels of health across racial groups. For instance, hypothesizing SES differences, place differences, or the additional exposure of Blacks to stress (e.g. discrimination) as the only causes of health disparities are over-simplistic. If that were true, equalizing SES, eliminating segregation, or eliminating discrimination would eliminate the Black-White gap in health. We argue that the picture is more complex: that part of these disparities will persist even if racial groups become equal in SES, place, and stress, because increasing SES is generates less health gains for Blacks than Whites.

In other words, we should not assume that there might be a third factor, or a set of third factors, that would simply explain (i.e., mediate) the effect of race on health. Therefore, it is not either race or SES but race and SES that generate the lower health status of Blacks compared to

Whites. Supporting our results, Navaro (1990) has argued that it is “race and class” not “race or class” that explain health disparities. This is in contrast to the traditional view that third factors such as SES, place, or stress that covary with race and health may fully explain the effects of race on health (Lantz, House, Mero, & Williams 2005; Miller & Taylor 2012). Although “differential exposure” also plays a major role in shaping health disparities, the role of “differential effects” should not be overlooked. We argue that racial differences are not solely due to additional exposure to low SES or stress; rather at least some of them are due to the “diminished gain” experienced by Black people in the US, as well as other disadvantaged groups.

The protective health effects of psychosocial resources (e.g., education, employment, and neighborhood) and psychological assets are unequal between the socially privileged and the economically disadvantaged groups. The ability of a group to take advantage of any additional resource is conditional on other protective factors that are available to them. The effects of social and economic resources are diminished for Blacks due to structural factors, such as poverty, segregation, racism, and discrimination, hinder their ability to navigate the system and take advantage of new resources that become available to them (Krieger, 2012; Gee, & Ford, 2011;

Williams & Mohammed, 2013; Agency for Healthcare Research & Quality, 2015).

A Paradoxical Effect

An interesting implication of the greater health gains from certain resources among Whites compared to Blacks is that, following this logic, Whites should also experience greater health loss

than Blacks when economic resources are reduced or eliminated. Data from national surveys on the impact of SES on health confirm this. That is, Whites gain more from a higher SES and lose more from a lower SES. Whites may also do worse than Blacks under conditions of adversity such as economic depression. For example, low education (Assari & Lankarani, 2016a) and living in poor neighborhoods (Assari, 2016a) reduce the life expectancy of Whites more than they do Blacks.

Unemployment is associated with the largest decline in life expectancy among White men, while

Black men lose minimum life expectancy due to unemployment (Assari, 2017a).

One method of examining the relative impact of certain protective and risk factors on health is to study the slopes when health is regressed onto these factors. Greater slopes can be interpreted as an indicator of relative advantage, but they reflect vulnerability (DiAngelo, 2011). As most social risk and protective factors show greater slopes for Whites than for Blacks, Whites’ health seems to be more dependent upon presence of SDH and SES than Blacks. Stressful life events can also have larger effects on depression in Whites as compared to Blacks (Assari & Lankarani 2016d). For example, Whites have shorter life expectancies than Blacks when they have few positive emotions

(Assari, Moazen-Zadeh, Lankarani, & Micol-Foster, 2016), poorer anger control (Assari, 2016b), lower self-efficacy (Assari, 2017c), and lower sense of agency (Assari, 2017d). Also, poor sleep (Assari,

Sonnega, Leggett, & Pepin, 2016) and negative emotions (Assari, & Lankarani 2016c) have larger effects on the incidence of chronic disease for Whites compared to Blacks. These papers collectively suggest that health costs associated with fewer psychological assets are greater for Whites than

Blacks.

Malat, Mayorga-Gallob, and Williams (2017) propose that Whites’ greater vulnerability to risk factors relative to Blacks may be due to their higher social status and greater privilege. That is,

they may be less prepared than Blacks to respond to social and economic adversity. Thus, the Black-

White difference in resilience in the face of unexpected difficulties is due to social rather than biological processes. However, vulnerability can be conceptualized as a cost of social privilege to

Whites, and resilience can be thought of as a gift of adversity. In this view, vulnerability is secondary to the lack of preparedness of Whites to cope with adversity, given their social privilege overall.

Compared to Blacks who have dealt with a wide range of economic and social stressors for centuries,

Whites are less resilient to adversity (Keyes, 2009). An example of this lack of preparedness is the recent increase in death of despair (i.e. death due to suicide, overdose, and substance use) in White

Americans documented by Case and Deaton (2015). They found that low SES Whites, particularly low

SES White men, have recently experienced an increase in mortality due to high-risk behaviors.

Research by Geronimus et al., (2015) also showed that adversity is associated with shortening of telomere length in Whites but not Blacks.

In contrast, many Blacks have found ways to manage their harsh environment, which may have helped them to develop a systematic resilience (Keyes, 2009), a phenomenon also called

“Blacks’ flourishing” (Keyes, 2009; Ryff, Keyes, & Hughes, 2003). This hypothesis about Blacks’ resilience is in line with an extensive theoretical and empirical body of work regarding resilience

(Lyons, Parker, Katz, & Schatzberg, 2009), defined as succeeding in the face of adversity

(Zimmerman, Ramirez-Valles, & Maton, 1999). In this view, the social group that experiences adversities gradually becomes more efficient in mobilizing their available assets and resources to protect the individual and mitigate the impact of risk factors. As a result, despite several social and economic risk factors, Blacks may maintain their sense of well-being. This is also consistent with recent studies showing that Blacks with depression maintain higher levels of hope (Assari, &

Lankarani. 2016e), positive emotions (Lankarani, & Assari, 2017), and mastery (Assari, & Lankarani

2017f) compared to Whites.

Thus, at a minimum, we can conclude that some health disparities are shaped outside of the healthcare system. The U.S. social structure continually generates gaps between social groups. We argue that there is a significant parts of health disparities which are caused by the very nature of

American social structure and how it functions. Unless this social structure is altered, racial health disparities will continue to grow. According to this explanation, disparities develop even before health care is needed. This suggests a needed shift in attention from a medical to a sociological model of health disparities. In the absence of any change, the U.S. social system will continue to generate smaller health gains from the same resources and assets for Blacks compared to Whites.

While the gain is conditional on race, it is difficult to close racial gaps in health, without altering how the operation and functionality of the macro level system. In its current form, American society, even with equitable access to resources across social groups, results in reliable health disparities between the socially privileged and disadvantaged groups.

It is not wise for policy makers, evaluators, and others to assume that socioeconomic resources and assets will influence the health of all social groups equally, as risk and protective factors interact with sociodemographic characteristics on health (Mehta & Preston, 2016). As a result, there is a need to systematically test all potential interactions between race, ethnicity, and

SES as indicators on health outcomes (Williams & Collins, 1995; Kessler & Neighbors, 1986).

Disparities seem to be larger at the highest levels of SES, suggesting that a diminished gain may be greater at higher SES levels (Farmer & Ferraro, 2005). However, due to the substantial covariation between race and SES, and also due to residual and unmeasured confounding variables (i.e.

epidemiologic terms that indicate biases due to an inability to cancel the effects of all potential covariates / confounders), it is exceedingly challenging to decompose the effects of race and SES on health (Kaufman, Cooper, & McGee, 1997). In addition, residual and unmeasured confounding variables are a common threat to the validity of research on the effects of race and health (Fewell,

Davey Smith, & Sterne, 2007). In many studies where the individual level, but not community level

SES is measured, higher level SES may be an unmeasured confounder.

The Impact of Economic Inequalities of the Racial Health Gap

The racial gap in health may widen in the future as has happened before. Williams and

Collins (1995) have provided a historical review regarding the widening of the racial gap in mortality and other health outcomes as a function of changes in economic conditions. They showed how a decline in Blacks’ economic well-being and an increase in Black-White economic inequalities resulted in a widening Black-White health gap across a number of health indicators. For example, between

1980 and 1991, the racial life expectancy gap grew from 6.9 years to 8.3 years. Black men and women’s life expectancy significantly declined from 1984 to 1989 (National Center for Health

Statistics, 1994; Williams & Collins, 1995). The age-adjusted Black to White death ratio increased from 1980 to 1991, with the annual excess of deaths increasing by 6,000 in Blacks compared to

Whites. During the same period, the age-adjusted death rate decreased more rapidly for American

Whites than for American Blacks (Williams & Collins, 1995). Freeman (1993) used mortality data over this 20-year period from 1960 to 1980 in Harlem, New York, and Blacks and Whites on the national level. Although there was a steady decline in national mortality rate; there was no considerable gain in life expectancy for Blacks who lived in Harlem, New York, over the same period. There were also differences in the incidence of certain diseases. For example, the decline in the incidence of heart

disease was less for Blacks compared to Whites, which likely resulted in a widening of the racial gap in life expectancy (Kochanek, Maurer, & Rosenberg, 1994). The racial health gap widens when the racial economic gap widens. In the 1980s, the ratio of Blacks earnings to White earnings was smaller, relative to the ratio of earnings in the 1970s. In concert with the widening of the economic gap, racial health disparities also widened for a range of health indicators (Williams & Collins, 1995). From

1984 to 1989, while the life expectancy of Whites showed a consistent increase, the life expectancy of Blacks declined (Williams & Collins, 1995).

Between 1960 and 1984, the protective effect of education against the risk of mortality increased substantially for White but not Black men (Feldman, Makuc, Kleinman, & Cornoni-Huntley,

1989). The gap in rate of mortality among groups of differing levels of SES increased from 1960 to

1986 (Pappas, Queen, Hadden, & Fisher, 1993). From 1969 to 1989, breast cancer mortality declined for high SES women, however, the mortality rate increased for low SES women during the same period (Wagener & Shatzkin, 1994). From 1980 to 1991, preterm delivery and low birth weight increased among Black women, while the same statistics remained unchanged for White women.

This resulted in a widening of the racial gap in infant mortality rates during this period (Rowley &

Hogue, 1993). There was also widening of the racial gap in the rates of sexually transmitted diseases from 1980 to 1991 (Castro, 1993).

These are all historical examples of the racial health gap widening as a direct result of economic factors. Widening of the racial gap is not limited by or specific to a single health outcome, as it has occurred across domains, and spillover effects may impact multiple health domains. In the absence of political and public policy changes working to address higher level societal and structural

factors such as residential segregation and institutional racism, Blacks are unlikely to gain from resources at the same level as Whites (Assari, 2017e).

Possible Mechanisms behind Differential Effects

The following section discusses five potential mechanisms behind the “diminished gain” or

“differential effects” experienced by Blacks. These mechanisms include: 1) labor market preferences and practices, 2) income and wealth generation and purchasing power, 3) interpersonal, institutional and structural discrimination, 4) cumulative gain due to initial advantage, and 5) extra cost associated with upward social mobility among Blacks. These mechanisms operate across levels and range from public policies to individual characteristics). While some of these explanatory mechanisms are related to the social structure and operate at the macro level, some others may predominantly exert their effects through group or individual levels. They are interconnected as the labor market may result in racial gap in income, and racial differences in purchasing power may cause upward social mobility of Blacks to be more costly. Additionally, these mechanisms are not mutually exclusive, and some may be more relevant than others depending on the resource and asset, age group, cohort, and racial group. For instance, differential life expectancy gain from education and employment are mostly due to racial differences in education quality and labor market practices. Interpersonal discrimination, however, may offer a better explanation for why high

SES may not protect Black men against depression (Assari 2017g).

Labor Market Preferences and Practices

At least some of Blacks’ diminished health return of SES is due to the smaller effect of education on employment and income for Blacks compared to Whites, which is due to racism in the labor market. From 1954 until 2013, Black unemployment rate has been consistently double that of

Whites (Desilver, 2013). When Blacks do find employment, due to the existing racial gap in pay, they earn less than Whites (Jencks & Mayer, 1990). They also enter different types of occupations from

Whites, as Blacks more commonly enter occupations that increase their exposure to environmental risk factors (U.S. Department of Labor, 2011). Blacks must often take minimum wage, repetitive jobs that increase their risk for poor mental health, substance abuse, and health problems (O’Campo &

Rojas-Smith 1998). As a result, an increase in education and employment may result in more tangible health gains for Whites than Blacks (Monnat, 2014).

The labor market is one of many American institutions that suffer from structural and institutional racism (Huffman & Cohen, 2004). Compared to White counterparts, college-educated

Blacks are much less likely to be employed, which reduces any health gain from employment

(Wilhelm, 1987). The income gap is larger at higher levels of education. In 2006, among men with a master’s degree, Blacks earned $27,000 less than Whites (IWPR 2010). Despite a similar job experience and education, employed Blacks are more routinely exposed to occupational hazards and carcinogens than their White counterparts (Williams & Collins, 1995). These differences all serve to explain why education and employment result in smaller health gains for Blacks.

Income and Wealth Generation and Purchasing Power

Income (i.e. the flow of economic resources to the household or family) and wealth (i.e. the reserve of economic resources) are both lower in Blacks than Whites. In fact, higher wealth of

Whites may explain why the same income results in smaller health gains for Blacks than Whites.

Across the same levels of income, Black households have less wealth, which has enormous direct and indirect implications for health across generations (Oliver, & Shapiro, 2006). In the Fragile

Families and Child Well-being Study (FFCWS), family SES at birth better protected White youth

against poor self-rated health (SRH) and high body mass index (BMI) than it did Black youth. That is, an increase in family SES at birth was a better promoter of future health for White youth than Black youth (Assari, Thomas, Caldwell, & Mincy, 2017). These papers suggest that diminished gain starts early in life, and includes multigenerational aspects (parental SES on offspring health).

Lower accumulation of wealth in Black families is cited as the result of a long history of racism and discrimination (Oliver & Shapiro, 2006). As houses are major assets, and location is the major determinant of housing value (Shapiro, 2006), residential segregation has played a major role in shaping the racial gap in wealth (Oliver & Shapiro, 2006). In addition to wealth differences, enormous racial differences also exist in income generation. Compared to Whites, Black households have a higher tendency to rely on multiple earners who collectively contribute to the total household income (Dressler, 1993). Among middle-class families, Blacks are more recent and less established in their social class, compared to Whites, which diminishes their health gains from social class (Collins, 1983).

As argued by Marmot (2015), how social groups can expend their available resources may be even more important than their SES resources. At any given income or wealth level, Blacks have lower purchasing power than Whites. Due to residential segregation, food deserts, and limited access to high quality resources in inner cities, Blacks must accept paying a higher price than Whites for the same goods and services (Williams, Priest, & Anderson, 2016).

Discrimination

One mechanism that offers an explanation for the diminished health gain of Blacks from SES resources is discrimination (Hudson, Bullard, Neighbors, Geronimus, Yang, & Jackson, 2012).

Discrimination negatively impacts a wide range of health outcomes (Mays, Cochran, & Barnes,

2007). Chronic exposure to discrimination increases risk of psychiatric disorders (Hope, Assari, Cole-

Lewis, & Caldwell, 2017). Additionally, experiencing discrimination carries consequences for physical health including higher rates of heart disease (Lewis, Williams, Tamene, & Clark, 2014), hypertension

(Mezuk, Kershaw, Hudson, Lim, & Ratliff, 2011), obesity (Hickson, et al., 2012), and mortality

(Barnes, de Leon, Lewis, Bienias, Wilson, & Evans, 2008). Discrimination also influences biological markers such as cortisol levels, which reflect stress responses (Lee et al., 2017), oxidative stress, which reflects inflammation (Szanton et al., 2012), and telomere length, which reflects aging (Chae et al., 2014). Given the recent trends in the racist rhetoric and public presence of White supremacy, discrimination may have a growing impact in American society in the coming years. Events such as those in Charlottesville and Ferguson suggest that racism and discrimination are still present in the

United States.

Discrimination also minimizes the health gains from SES resources (Hudson, Bullard,

Neighbors, et al. 2012). Hudson, et al., (2012) found the protective effects of SES among Black adults are smaller in the presence of discrimination. Assari and Caldwell (2017c) also used a national sample of Black youth and found that discrimination has a stronger effect on Major Depressive

Disorder (MDD) of Black boys with higher levels of SES compared to low levels of SES. This finding is supported by other research which has shown that discrimination is more consequential for Black males than Black females (Assari, Lee, Nicklett, Moghani Lankarani, Piette, & Aikens, 2017). The

Black men most vulnerable to MDD as a result of discrimination also hold high hegemonic masculinity beliefs (Caldwell, Antonakos, Tsuchiya, Assari, & De Loney, 2014).

Discrimination is not limited to between individuals. Blacks are systematically discriminated against in educational and correctional settings. Historically, race has had an effect on education in

the United States (Grogger, 1996; Steele 1992), with Blacks typically attending lower quality schools

(Card & Krueger, 1992). Both individual level race and racial composition of schools are major determinants of educational resources and schooling quality (Roscigno & Ainsworth-Darnell, 1999).

Exclusionary disciplines are disproportionately applied to Black children (Fenning & Rose, 2007). The result is huge Black-White gaps in school performance (Jencks & Phillips, 2011). Due to an increased risk of discrimination from their teachers (Noguera, 2009), Black boys are at an exceptionally high risk of school dropout (Rumberger, 1983), which contributes to the school to prison pipeline (Wald,

& Losen, 2003). Seaton and Douglass (2014) showed that Black youth report a daily average of 2.5 discriminatory events that increase their depressive symptoms on the following day. Another institution that systematically discriminates against Blacks is the banking system (Ross, & Yinger,

2002). Black families often pay much higher interest rates on their mortgages than do White families. According to the Home Mortgage Disclosure Act (HMDA) data, even high-income Blacks pay more subprime (high) mortgage rates than comparable high-income Whites (Bocian, Ernst, & Li,

2008). Mortgage discrimination will directly result in Black-White differences in foreclosure rates

(Bocian, Li, & Ernst, 2010).

Cumulative Disparities Due to Initial Advantage

Gains are typically larger for the “Haves” (i.e. the majority and the social advantaged groups) than the “Have-Nots” (i.e. the minority and marginalized groups that are at economically disadvantage conditions) (Ceci & Papierno, 2005). As a result, policy makers, program planners, and evaluators should be aware that many interventions that increase overall access of the society to resources may not reduce disparities between groups. This is possibly because socially and

economically privileged groups are better equipped to capitalize on new programs that become available to them, compared to marginalized groups.

An initial advantage, characterized by the availability of SES resources and cognitive assets

(coping and affect), disproportionately advances the majority group, explaining why Whites gain more than Blacks from any additional resources later in life (Ceci & Papierno 2005). Over time, this disparity accumulates, widening pre-existing gaps between social groups and their ability to gain from available resources and assets. As stated in the Cumulative Advantage Theory, having an initial advantage results in further cumulative advantage, and an initial disadvantage is accentuated over time (Shaywitz, Shaywitz, Pugh, & Constable, 1995).

Nonequivalence of childhood SES has been used to explain why high SES during adulthood is less protective for Blacks than Whites (Warner & Hayward, 2006; Colen, 2011). Holmes and Zajacov

(2014), for example, attributed differential health effects of SES resources across races to racial differences in childhood SES. There are, however, studies whose findings do not support such an explanation (Brown, O’Rand, & Adkins 2012). Overall, it has not been determined whether or not racial gap in childhood SES is exclusively responsible for the differential health effects of adulthood

SES.

Cost of Upward Social Mobility

To climb the social ladder, Blacks have a tendency to use effortful coping (Sellers, &

Neighbors; 1999). Blacks report high levels of goal-striving stress (Sellers, & Neighbors, 2008) defined as the “discrepancy between aspiration for and achievement of a better way of life, weighted by the subjective probability of success, and the level of disappointment experienced if those life goals were not realized” (Neighbors, Sellers, Zhang, & Jackson, 2011, p. 51). One example is John

Henryism, a well-studied, effortful coping strategy that is commonly exercised by Black men to deal with discrimination in their daily life and aid in upward social mobility. John Henryism is, however, not the only form of coping that Blacks use for upward social mobility. Blacks and Whites employ different coping strategies to deal with stress (Conway, 1986). For instance, compared to Whites,

Blacks have a higher tendency to rely on social support and religion to cope with adversities (Reevy,

& Maslach, 2001).

Effortful coping strategies come with psychological and physiological costs (Bennett, et al.,

2004; James, 1994; Sellers & Neighbors, 2008). Although most of the literature has focused on the undesired mental health effects of John Henryism (Hudson, et al., 2016), the health risk associated with John Henryism goes beyond merely a psychological cost (James, Strogatz, Wing, & Ramsey,

1987). Whether John Henryism promotes health or impairs health seems to depend on one’s access to other resources such as SES and social support (Hudson, et al., 2016). John Henryism may function as a resource or as a health hazard (Mujahid, James, Kaplan, & Salonen, 2017). John Henryism is most damaging when it covaries with low access to SES resources and social support (James, 1994).

John Henryism increases cardiovascular risk (Mujahid, James, Kaplan, & Salonen, 2017). As a result,

John Henryism may have a unique role is shaping health disparities, particularly in higher SES levels.

These processes could explain the smaller health gain due to educational achievement for Blacks compared to Whites (Fuller-Rowell, Doan, and Eccles, 2012).

Policy Implications

This section discusses potentially relevant social and economic policies based on the findings discussed above. Unlike other resources discussed, income has similar effects on mortality among

Blacks and Whites (Assari & Lankarani, 2016a; Fedewa, McClellan, Judd, Gutiérrez, & Crews, 2014).

Thus, we believe that income redistribution policies are a central policy strategy to reduce Blacks’ diminished gain. Second, it is necessary to distance ourselves from any policy or program that stimulates or supports widening of the racial health gap. Simultaneously, there is a need to enforce policies that reduce tolerance for discrimination at all levels against Blacks and other minority groups. As equal access generates differential impact across populations, policy solutions should go beyond simply equalizing access and address barriers in the life of Blacks. These policy solutions should be at multiple levels (e.g. individual, organizational, and institutional levels). Finally, we argue that religion and social support should be leveraged as they show particularly beneficial effects among Blacks.

Income Redistribution Policies

As just noted, income is one of the few exceptions to the Blacks’ diminished health return

(Assari & Lankarani, 2016a; Fedewa, et al., 2014). While many SES indicators and/or psychological assets better protect Whites than Blacks (Table 1), each unit increase in income shows the same increase in life expectancy for Whites and Blacks (Assari & Lankarani, 2016a). The observation that all groups similarly gain health from income is very promising and argues for income redistribution policies as a main solution to close the racial gap in health. For example, policy solutions may include

1) increasing the minimum wage for jobs often occupied by Blacks, 2) reducing the racial wage gap in the U.S. labor market, and 3) tax policies that help low income families to accumulate more wealth over time. Helping Blacks achieve higher incomes may be one of the most effective solutions to health disparities, given income is one of the fewest economic resources that similarly translates to health gain, regardless of race (Assari & Lankarani, 2016a). There is empirical evidence suggesting that income redistribution predicts well-being (Cheung 2017). Countries where income is distributed

evenly have a higher level of health status (Kawachi, & Kennedy, 1997). This is particularly important as Blacks are over-represented in low paying jobs. Policies providing temporary financial incentives and cash assistance may also have a role in addressing needs of people in deep poverty (Bitler &

Hoynes, 2016).

Avoiding Policies that May Widen the Health Gap

A critical step to reduce the health gap is avoiding policies or programs that disproportionately improve the health of the socially advantaged majority group. Policy analysts who evaluate the impact of social policies should consider the differential effects of the same policies on

Whites and Blacks, in addition to evaluating the overall effects on the total population. There is also a particular need to identify policies that minimize Blacks’ diminished return (Lorenc & colleagues,

2013). It is important to identify sub-population differences in factors that alter the uptake and impact of the interventions across population sub-groups. Some of the factors that impact service provision or access of interventions across sub-groups include differential intervention efficacy, population variation in trust and acceptability of the program, as well as variation in compliance

(Lorenc et al., 2013). Low trust, poor participation rate, and low adherence of Blacks can be traced to historical factors such as formal racist laws and informal racist social customs (Kennedy, Mathis, &

Woods, 2007). To regain Blacks’ trust, there is a need for considerable efforts and investments at all levels in the healthcare system and other institutions.

Zero Discrimination at All Levels

More legislation is required to reduce discrimination. Additionally, stronger enforcement of existing anti-discrimination policies should be in place. To reduce the ongoing structural discrimination in education quality (Roscigno & Ainsworth-Darnell, 1999), we must invest more in

the schooling and education of Blacks (Card & Krueger, 1992). Such investments may help schools reduce discrimination against Black children, and specifically address school dropout rates among

Black boys (Rumberger, 1983). A particularly supportive policy would be the education of teachers and principals of predominantly Black schools to reduce disproportionate disciplinary actions against

Black boys (Fenning & Rose, 2007). Teachers who work at majority Black schools, in particular, should receive training to minimize discrimination and bias among teachers, particularly against

Black boys (Noguera, 2009). Governmental or state level policies should minimize disparities in availability of educational resources across social groups (Jencks & Phillips, 2011). Systematic evaluations of educational systems are necessary to monitor how these policies reduce the existing gaps in school performance between the majority and minority populations. Policies and programs that increase education quality in majority Black schools, particularly those that are least resourced

(Grogger, 1996), may increase protecting effects of education on health of Blacks. Such investment would produce returns in community growth due to the salient role of education quality in the economic growth of our communities (Hanushek & Wößmann, 2007).

Similar to the educational system, we must abnegate discrimination in other sectors such as banking, housing, the correctional system, and policing. Federal enforcement agencies have the responsibility to more stringently enforce the existing anti-discriminatory laws, such as fair lending laws. Such careful monitoring may reduce discrimination across systems (White, 2009).

Going Beyond Equalizing Access

As equal resources and assets result in unequal gain (Assari, 2017e), social, public, and economic policies that merely equalize distribution of populations to resources and assets, but ignore the barriers not equally distributed across social groups, may unintentionally exacerbate

existing racial and SES health inequities. Despite good intentions, such universal policies do little to reduce, and even have the potential to aggravate, the racial health gap in the United States. Policies should go beyond universal investments. Any policy that over-emphasizes equal access without considering the structural barriers that maintain the relative disadvantages of Blacks should be regarded as a policy which risks widening the racial and SES health gap. Given the greater likelihood of Whites to derive benefits from any additional resource, programs should include racial comparisons in their evaluations and ensure that no social group is left behind in translating those resources to tangible and measurable health gains.

One solution is to consider more tailored interventions and programs that address the specific needs of Blacks and other marginalized groups. Policies should target the societal and structural barriers and constraints that limit Blacks’ ability to convert their available economic resources and psychological assets into health outcomes. Policies should address socioeconomic barriers prevalent in the life of Blacks who live in urban communities with limited resources.

Simultaneously targeting barriers and providing additional resources may increase the efficacy and return of investment of any social or economic policy, which would, cumulatively, reduce racial health disparities.

With specific regard to employment and education policies, significant attention should be given to the quality of education, type of occupation, and income generated by such resources.

Education and employment initiatives that disregard the deeply rooted structural and societal inequalities that Blacks face will not be sufficiently impactful.

In addition, there is a need for purposeful policies to reduce the racial residential segregation that still exists in the United States. Such segregation operates as structural and

contextual barriers in the lives of many Blacks today. A majority of Black neighborhoods are distant from high paying jobs and high-quality education (Lewis, James, Hancock, & Hill-

Jackson, 2008). In addition, the disproportionate number of fast food restaurants and liquor stores in black neighborhoods are responsible for increasing risks of obesity and chronic diseases such as stroke, hypertension, and diabetes for Blacks (Morgenstern, et al., 2009).

Black neighborhoods are also poor in resources for health care. Finally, social disorder, crime and gang violence limit the ability of Blacks in urban areas to thrive (Thomas, Caldwell,

Assari, Jagers, & Flay, 2016).

Discriminatory lending practices still continue. The existing anti-discrimination laws in lending practices must be imposed more dependably. To minimize discriminatory lending practices does not require new laws, but simply a better implementation and enforcement of the existing laws. Equitable economic policies have a unique importance in preventing health disparities between the social groups. Discriminatory mortgage and loan practices that exist should be prohibited. If needed, new policies should prohibit higher bars and more restricted thresholds that

Blacks must meet to qualify for loans. Policies should also enforce equal interest rates and mortgage down payments for Blacks and Whites (Pager & Shepherd, 2008).

As already established, without extra help, Blacks will have difficulty competing with Whites to secure high paying jobs and educational opportunities. Our findings expand on the past research and conclude that comparable resources consistently generate less positive impact on the lives of

Blacks compared to Whites. These results advocate for the implementation of affirmative action policies. However, affirmative action is one of the most controversial public policies that focuses on the redistribution of resources and opportunities (Katz & Taylor, 2013). In the view of many Whites,

affirmative action is reverse discrimination (Dansby, 1996), and not every group views it as fair and just (Peterson, 1994). These counter concerns make affirmative action politically charged, particularly in the current political climate (Crosby, 2004). As a result of this resistance, it is very difficult to get bipartisan political support for affirmation action policies. Still, there is a need for reevaluation of the actual effects of affirmative action policies (Rabinowitz, Sears, Sidanius, &

Krosnick, 2009) and its impact on groups not targeted by affirmative action policies and practices.

Affirmative action would still seem to offer one powerful remedy to the differential exposure and differential gain typically experienced by Black people in the US.

Policy analysts should investigate the gap-widening potential of interventions and policies that only increase the access of populations to resources. Given that the system prefers Whites to

Blacks, and given the current political climate, interventions may elevate the economically advantaged populations to a greater degree than their less advantaged counterparts. It is the responsibility of researchers to study in which conditions a policy can inadvertently widen the existing racial and SES gaps (Ceci & Papierno, 2005). Lorenc et al., (2013) reviewed public health interventions aimed to promote the overall health of the population, but are at risk for increasing inequalities. They called such programs Interventions-Generating Inequalities. Although media campaigns and workplace smoking bans have the potential to generate inequalities, provision of resources; fiscal interventions (e.g. tobacco pricing), and structural workplace interventions are likely to reduce the racial and SES gaps. Graham and Kelly (2004) have provided conceptual and theoretical frameworks that help to identify interventions-generating inequalities. Lorenc et al.,

(2013) also distinguish the ‘upstream’ interventions that focus on social or policy-level determinants such as reducing price barriers from ‘downstream’ interventions that focus on individual factors such as education. Overall, Lorenc et al., (2013) argue that downstream interventions do not appear to

reduce inequalities, and may increase them. They propose that upstream resource provision interventions may effectively reduce disparities.

Policy Responses Should be Multi-level

Given that we attribute most of the findings we have reported as due to various kinds of racism, we suggest that the solution should be multi-level and target all aspects of racism that hinder Blacks’ lives. This section reviews how Williams and Mohammed (2013), Bailey et al., (2017),

Reskin (2012), and Gee & Ford (2011) conceptualized Black-White health disparities as the byproduct of the structure and function of American society. Williams and Mohammed (2013) have argued that racial disparity is a product of multi-level processes. They theorize a wide range of procedures by which racism adversely impacts the health of Blacks. Institutional racism systematically reduces Blacks’ access to safe and high-quality housing, neighborhood, schooling, employment, and other desirable material and human resources in society (Williams & Mohammed,

2013). Bailey et al., (2017) define structural racism as “the totality of ways in which societies foster

[racial] discrimination, via mutually reinforcing [inequitable] systems..(e.g. in housing, education, employment, earnings, benefits, credit, media, health care, criminal justice, etc.) that in turn reinforce discriminatory beliefs, values, and distribution of resources”, (p. 1455) reflected in history, culture, and interconnected institutions.

Building on a systems perspective, Reskin (2012) defined racism as a discrimination system that constantly generates racial disparities across several life domains including but not limited to schooling, housing, residential location, employment, health, credit, banking, lending, and justice.

Gee and Ford (2011) also argue that racial health disparities have structural, rather than individual causes. Societal and structural factors such as social segregation and economic policies that operate

through intergenerational mechanisms are responsible for health inequalities. As a result, policy solutions should attack a wide range of dimensions of the social structure as they collectively result in health disparities (Gee & Ford, 2011). Reskin (2012) argues that an appropriate response should include policies and interventions that operate simultaneously across subsystems, and directly challenge all the processes of racism across the subsystems in which racism operates. Thus, to eliminate health disparities, policy solutions should consider the reciprocal interrelations between the components of the integrated system that is generating the health disparities. All these require better representation of Blacks in high-level policy making, which itself depends on an increase in political participation (e.g. voting) of Blacks and other minority populations (Hamilton & Ture, 2011).

Geronimus, et al., (2016) introduced the “Jedi Public Health (JPH)” as one solution to the effects of racism. This framework, “…focuses on changing features of settings in everyday life, rather than individuals, to promote population health equity, a high priority, yet, elusive national public health objective” (p105). Geronimus et al., (2016) have argued that there is a need for expansion as well as a re-orientation of efforts to eliminate population health inequities. In the JPH framework, policies and interventions should remove all the discrediting cues in daily life of Blacks and other minority groups. Such Jedi Public Health policies will disrupt the continuously harmful physiological and psychological processes that fuel racial health inequities.

The appropriate policy response would include a wide range of multi-level policies that operate across various sub-systems. Policies that target societal, as well as individual level, discrimination are needed. There is a need for policies that improve neighborhood safety as well as those that increase availability of educational resources at majority Black schools. Policies should increase access and improve the quality of medical care for Blacks. These policies, and others, would

help Blacks take control of their lives, which has implications for improving their health (Williams &

Mohammed, 2013). In a seminal paper published recently in the journal Lancet, Bailey et al., (2017) argue that efforts to dismantle structural racism have historically encountered serious resistance from institutions, communities, and individuals seeking to preserve their racial privilege. They argued, however, that a focus on structural racism would be a concrete, feasible, and promising approach towards advancing health equity in United States.

Leveraging Religion and Social Support in Communities

While Blacks gain less than Whites from several economic resources and psychological assets, religion and social support are exceptions to this general rule. Increases in religious involvement and social support provide larger health gains for Blacks compared to Whites. Several studies have documented Blacks’ advantage in gaining health from religion and social support

(Lincoln, Chatters, & Taylor, 2003). To give an example, religious attendance is associated with 13 and seven extra years in life expectancy for Blacks and Whites, respectively (Hummer, Ellison,

Rogers, Moulton, & Romero, 2004). In a national sample, church-based social support fully mediated the effect of religious involvement on the well-being of Blacks but not Whites (Assari, 2013). Each unit of increase in positive social relations had a larger protective effect against depression for Blacks than Whites (Lincoln, Chatters, & Taylor, 2003). Church has also become a source for forgiveness, resilience, and very strong relations with God, which all protect the health of Blacks. In addition to a place of worship, the church has traditionally been a social institution that provides goods and tangible services for Black families, regardless of social status (Krause, 2002).

Social relations are also more extended in Blacks than Whites as they include supportive relations from fictive kin relations (defined as social ties that are based on neither consanguineal

(blood ties) nor affinal ("by marriage") ties [Ebaugh & Curry. 2000]), friends, and community members (Taylor & Chatters, 1991). Thus, social support and religion might have operated historically as cultural refuges by Black communities to cope with oppression and economic adversity. Although it is plausible to argue that Blacks have mastered their ability to mobilize their social support, research is still needed on whether social support and religion can mitigate Blacks’ diminished return or not. However, these findings argue for allocating additional resources for promotion of positive family relations, extended social relations, and faith-based programs in Black communities. Although it is not easy to draw a causal inference between religious involvement and health, and reverse causality is always a concern (healthier individuals may attend church more frequently), the association between various aspects of religion and health are stronger for Blacks than Whites.

All this said, we recognize that given the current political climate, there are enormous barriers to the implementation of the policies discussed. It is always easier to describe than solve the problem. However, as stated by David Williams (2012) as a society, we need to demand and challenge the current political system for appropriate alleviative policies that are needed for an equitable society.

Theoretical Implications

This review shows that although Blacks suffer worse physical health outcomes, their minority status per se does not reflect greater physical or psychological vulnerability (Dowd &

Bengtson, 1978). As explained in this paper, it is Whites not Blacks for whom economic and psychological risk factors have systematically stronger effects. This pattern is indicative of Blacks’ resilience rather than vulnerability. This is important given that in discussing some health disparities,

scholars often use the terms vulnerable and minority populations interchangeably (Hutchinson, et al., 2007). For instance, Double Jeopardy (Dowd & Bengtson, 1978), Triple Jeopardy (Bowleg, Huang,

Brooks, Black, & Burkholder, 2003), and Multiple Jeopardy (King, 1988) and Multiple Disadvantage

(Grollman, 2014) hypotheses have traditionally conceptualized minority populations as vulnerable groups that are more susceptible to the effects of any additional risk factor (King, 1988). Most of these frameworks conceptualize synergistic effects of race and additional risk factors. The results reviewed in this paper, however, suggest that in most cases, race, per se, does not have synergistic effects with additional risk factors. In contrast to all these theories, this line of research has methodically documented Blacks’ systemic resilience instead of their vulnerability. The reason Blacks suffer worse health outcomes is not because they are vulnerable, but because they are disproportionately exposed to a large number of economic and social adversities, and have less access to economic and social buffers. Ironically, exposure and vulnerability move in opposite directions. The social group that experiences more exposures to risk factors at the same time actually shows a lower level of vulnerability.

As a social group, Blacks suffer poor health outcomes despite their consistent resilience to each individual risk factor. This phenomenon can be understood by the law of small effects (Brown, et al., 2014). According to this law, health disparities are not a consequence of a few large factors, but rather are shaped by multiple sets of smaller factors. Jackson, Govia, and Sellers (2010) have used the term “rule of small effects” to describe social origins of racial health disparities. Findings by our research team show that each risk factor results in a smaller health decline for Blacks than

Whites. While the term “rule of small effects” is still true, the phrase “rule of smaller effects” may be more accurate, as most of the effects are systematically smaller for Blacks, compared to Whites.

Research Implications

Further research is needed on population variation and mechanisms behind such variations in the effects of SDH and SES and the resulting health disparities due to such diminished gain. For instance, additional research is needed on differential social, psychological, and biological costs of upward social mobility among Blacks, particularly Black men (Fuller-Rowell & Doan, 2010). More research on relative contribution of the education system, labor market, correctional system, and segregation in shaping differential effects based on race. This is very important given the historic emphasis on the role of different distribution of SES and SDH (Marmot, Allen, Bell, Bloomer, &

Goldblatt, 2012) as causes of health disparity.

We also need to ascertain the most effective economic and social policies that enable diverse populations to equally gain from their available resources. Overall, we know very little about programs and policies that can undo “diminished return” (Farmer & Ferraro, 2005) or “differential effects” (Assari & Caldwell, 2017a) among Blacks. In addition, there is a need to identify and flag the interventions that have the potential to improve the health of the population overall but may widen the health inequalities and the gaps across population groups (Ceci & Papierno, 2005; Lorenc et al.,

2013). SES and SDH historically play a role in the causes of health disparity, thus in the interest of alleviating this health disparity, it is important to identify causes of this disparity across racial groups and to be able to identify and change social and economic policies that disproportionately favor the initially advantaged as opposed to the initially disadvantaged.

As the mechanisms that cause this health disparity across racial groups are complex and multifaceted, research into its many sides and their intersections, particularly research on the intersection of policy, social psychology, economics, sociology, and public health, is required. We still

do not know to what extent these differential effects are due to culture and what proportion of them are due to social structure (i.e., higher-level policies and procedures that are in place as a part of social structure and how the society functions as a system) (Krieger, 2012; Gee & Ford, 2011).

More research is also required in the areas of culture, gender, and individual behaviors to explain the effect of poverty and economic disadvantage on health.

There is also a need to study how culture and individual behaviors explain the effect of poverty and economic disadvantage on health. Culture and social norms may be particularly important in explaining Black-White differences in diet, obesity, and diabetes (Carter & Assari, 2017).

Racial and ethnic groups use different coping behaviors that are learned from their culture (LaVeist,

Thorpe, Pierre, Mance, & Williams, 2014). For instance, Black women may have a higher tolerance toward larger body sizes and obesity, as a cultural adaptation to economic adversity and neighborhood danger (Pope, Corona, Belgrave, 2014). As a result, larger body size is not perceived as obesity and may not initiate weight control behaviors in Black women, which has implications for high prevalence of obesity, even at higher SES levels (Assari & Lankarani, 2015). While Black women may have a higher tendency to turn to comfort food to cope with stress, Black men may have a higher tendency to turn to substances, particularly alcohol (Jackson, Knight, & Rafferty, 2010). These patterns may explain why high SES may fail to protect Black women against obesity (Assari, Nikahd,

Malekahmadi, Lankarani, & Zamanian, 2016). For example, Black men and Black women show different associations between obesity and depression (Assari, 2014). Surprisingly, depression reduces rather than increases the risk of obesity for Black men; this is not true for Black women

(Assari, 2014). These findings speak to the complex and multiplicative effects of race, gender, SES, culture, and behaviors on health (Assari. 2014).

Because of this complexity, future research should consider an intersectionality framework to study the non-linear and multiplicative effects of race, gender, and class on health. The concept that it is not simply race but the intersection of race, gender, and class, that shapes access to opportunity structure and the impact of stress is a cornerstone of the intersectionality framework

(Bauer, 2014). According to this theory, it is not each individual identity, but the intersection of multiple identities that determines exposures and vulnerabilities to risk and protective factors

(Collins, 2015; Hancock, 2007). This is supported by the considerable theoretical and empirical work on cultural moderation hypothesis (Markus and Kitayama 1991). Based on this hypothesis, cultural groups differ in the associations between SES, emotions, and health outcomes. For instance, the associations between SES, affect, inflammation, and health outcomes are also stronger for Whites than Asians (Kitayama & Park, 2010). Among Blacks, men and women differ in the type of health outcomes that follow their exposure to stress (Assari & Lankarani, 2017; Assari, Smith, Caldwell, &

Zimmerman, 2015).

Summary

Refuting the arguments that racial health disparities are due to biologically inherent deficits in Blacks (e.g., Herrnstein & Murray, 2010), this paper demonstrates that racial differences in health are due to social rather than biological processes. In contrast to the argument by Herrnstein &

Murray (2010) who conceptualize racial differences in assets due to biological (i.e. fixed and unmodifiable) factors, the current paper provides evidence that Black-White differences are primarily due to society’s hindrance of Blacks’ potential to achieve tangible gains from the resources in their environment. Blacks’ diminished health gain does not indicate an inability to use the resources that become available to them nor a mismanagement of assets. Rather, Blacks’ diminished

gain should be viewed as a consequence of American society’s historical mistreatment of Blacks.

Similarly, the larger effects of risk factors for Whites should not be interpreted as Whites’ fragility

(i.e., due to biology). The finding that Whites exhibit a greater health decline in response to a decline in resources should be attributed to their social dominance and having lived a privileged life.

Neither Whites nor Blacks should be blamed for the differential effects discussed here. Such differential effects are not innate but due to American social structure. Such differential effects will continue until structural racism in U.S. institutions is eliminated. Unless a drastic change is made,

Blacks and Whites will not similarly benefit from the same social and economic resources. In the absence of such changes, upward social mobility will be always associated with extra social, psychological, and physiological costs for Blacks compared to Whites. Of course, these findings should not encourage redirection of investments from Blacks to Whites, with the excuse that such investment would have larger returns.

In closing, we must acknowledge that most of the findings cited in this article are correlational. Thus, causality can be only suggested, but not proven. Many of these findings derived from longitudinal studies come with measurement biases, residual confounding variables, selection bias due to differential attrition, and low sample size for. These all threaten the validity of any causal conclusions. However, we do not believe these findings can be easily explained by methodological shortcomings, as they are robust across settings, predictors, outcomes, cohorts, and age groups. Further, the causal inferences made in this article seem to be the most reasonable and parsimonious interpretations of the associations we have reported.

It seems quite unlikely that ethical experimental studies in which, for example, resources are systematically provided to one group and not to another can ever be conducted. Perhaps,

however, more sophisticated analytical methods may permit stronger causal inferences. Such methods and further research on differential exposure and differential gain should provide us with more insight into the causes of racial disparities in health and lead to new policies to address these disparities.

SHERVIN ASSARI is an assistant professor of psychiatry and public health at University of Michigan

Ann Arbor. He holds joint appointments at Center for Research on Ethnicity, Culture, and Health

(CRECH), Poverty Solutions, and the Institute for Healthcare Policy and Innovation (IHPI). He studies the differential effects of social risk and protective factors by race, gender, class, and place. Instead of main and universal effects, his research has focused on how the intersections of race, ethnicity, gender, class, and place alter the social processes behind illness and health. With more than 15 years of post-graduate research experience, he has authored more than 200 peer-reviewed papers. He is an elected fellow of the New York Academy of Medicine (NYAM), Society of Behavioral Medicine

(SBM), and the American Academy of Health Behavior (AAHB). He has chaired committees and councils for American College of Epidemiology (ACE) and AAHB, and is currently the president of the

Scientific Association for Public Health in Iran (SAPHIR).

References

Agency for Healthcare Research & Quality. (2015). Population Health: Behavioral and Social Science Insights. Understanding the Relationship between Education and Health; http://www.ahrq.gov/professionals/education/curriculum-tools/population- health/zimmerman.html

Artiga, S., Damico, A., & Garfield, R., (2015). The Impact of the Coverage Gap for Adults in States not Expanding Medicaid by Race and Ethnicity. http://www.kff.org/disparities-policy/issue-brief/the- impact-of-the-coverage-gap-in-states-not-expanding-medicaid-by-race-and-ethnicity/

Assari, S. (2013). Race and ethnicity, religion involvement, church-based social support and subjective health in United States: a case of moderated mediation. International Journal of Preventive Medicine, 4, 208-17.

Assari, S. (2014). Association between obesity and depression among American Blacks: Role of Ethnicity and Gender. Journal of Racial and Ethnic Health Disparities, 1, 36-44. doi:10.1007/s40615- 014-0007-5.

Assari, S. (2015). Ethnic and gender differences in additive effects of socio-economics, psychiatric disorders, and subjective religiosity on suicidal ideation among blacks. International Journal of Preventive Medicine, 6, 53.

Assari, S. (2016a). Perceived neighborhood safety better predicts 25-year mortality risk among whites than blacks. Journal of Racial and Ethnic Health Disparities. doi: 10.1007/s40615-016-0297-x.

Assari, S. (2016b). Hostility, anger, and cardiovascular mortality among blacks and whites. Research in Cardiovascular Medicine, doi: 10.5812/cardiovascmed.34029.

Assari, S. (2016c). Psychosocial correlates of body mass index in the United States: Intersection of race, gender and age. Iranian Journal of Psychiatry and Behavioral Sciences, 10, e3458. doi: 10.17795/ijpbs-3458.

Assari, S. (2016d). Race and ethnic differences in additive and multiplicative effects of depression and anxiety on cardiovascular risk. International Journal of Preventive Medicine. 7, 22. doi: 10.4103/2008-7802.173931

Assari, S. (2017a). Life expectancy gain due to employment status depends on race, gender, education, and their intersections. Journal of Racial and Ethnic Health Disparities, doi: 10.1007/s40615-017-0381-x.

Assari, S. (2017b). Whites but not Blacks gain life expectancy from social contacts. Behavioral Sciences, 7, 68, doi:10.3390/bs7040068.

Assari, S. (2017c). General self-efficacy and mortality in the USA; Racial differences. Journal of Racial and Ethnic Health Disparities, 4, 746-757. doi: 10.1007/s40615-016-0278-0.

Assari, S. (2017d). Race, sense of control over life, and short-term risk of mortality among older adults in the United States. Archives of Medical Sciences, 13, 1233–1240. doi: 10.5114/aoms.2016.59740.

Assari, S. (2017e). Unequal gain of equal resources across racial groups. International Journal of Health Policy and Management, 6, 1-6. doi:10.15171/ijhpm.2017.902.

Assari, S. (2017f). Neuroticism predicts subsequent risk of major depression for whites but not blacks. Behavioral Sciences, 7, 64. doi:10.3390/bs7040064

Assari, S. (2017g). Combined racial and gender differences in the long-term predictive role of education on depressive symptoms and chronic medical conditions. Journal of Racial and Ethnic Health Disparities, 4, 385-396. doi: 10.1007/s40615-016-0239-7.

Assari, S., & Burgard, S. (2015). Black-White differences in the effect of baseline depressive symptoms on deaths due to renal diseases: 25 year follow up of a nationally representative community sample . Journal of Renal Injury Prevention, 4, 127-35.

Assari, S., & Caldwell, C. H. (2017a). The link between mastery and depression among Black adolescents; Ethnic and gender differences. Behavioral Sciences, 7, pii: E32. doi: 10.3390/bs7020032.

Assari, S., & Caldwell, C. H. (2017b). High risk of depression in high income African American boys. Journal of Racial and Ethnic Health Disparities, doi: 10.1007/s40615-017-0426-1.

Assari, S., & Caldwell, C. H. (2017c). Socioeconomic status a vulnerability factor among african american youth; a study of discrimination – depression link. Behavioral Sciences, In Press.

Assari, S., & Lankarani, M. M. (2015). The association between obesity and weight loss intention weaker among blacks and men than whites and women. Journal of Racial and Ethnic Health Disparities, 2, 414-20. doi: 10.1007/s40615-015-0115-x.

Assari, S., & Lankarani, M. M. (2016a). Race and urbanity alter the protective effect of education but not income on mortality. Front in Public Health, 4, 100. doi:10.3389/fpubh.2016.00100.

Assari, S., & Lankarani, M. M. (2016b). Education and alcohol consumption among older Americans; black-white differences. Frontiers in Public Health, 4, 67. doi: 10.3389/fpubh.2016.00067.

Assari, S., & Lankarani, M. M. (2016c). Chronic medical conditions and negative affect; racial variation in reciprocal associations over time. Frontiers in Psychiatry, 7, 140. doi: 10.3389/fpsyt.2016.00140.

Assari, S., & Lankarani, M. M. (2016d). Association between stressful life events and depression; intersection of race and gender. Journal of Racial and Ethnic Health Disparities, 3, 349–356. doi:10.1007/s40615-015-0160-5.

Assari, S., & Lankarani, M. M. (2016e). Depressive symptoms are associated with more hopelessness among white than black older adults. Frontiers in Public Health, 4, 82. doi: 10.3389/fpubh.2016.00082.

Assari, S, Lankarani, MM, & Burgard, SA, (2016). Black White difference in long term predictive power of self-rated health on all-cause mortality in United States. Annals of Epidemiology, 26, 106- 14. doi: 10.1016/j.annepidem.2015.11.006.

Assari, S., Burgard, S., & Zivin, K. (2015). Long term reciprocal associations between depression and chronic medical conditions; longitudinal support for black-white health paradox. Journal of Racial and Ethnic Health Disparities, 2, 589 – 597. doi: 10.1007/s40615-015-0116-9.

Assari, S., Lee, D. B., Nicklett, E. J., Moghani Lankarani, M., Piette, J. D., & Aikens, J. E. (2017). Racial discrimination in health care is associated with worse glycemic control among black men but not black women with type 2 diabetes. Frontiers in Public Health, 5, 235. doi: 10.3389/fpubh.2017.00235.

Assari, S., Moazen-Zadeh, E., Lankarani, M. M., & Micol-Foster, V. (2016). Race, depressive symptoms, and all-cause mortality in the United States. Frontiers in Public Health, 4, 40. doi: 10.3389/fpubh.2016.00040.

Assari, S., Nikahd, A, Malekahmadi, MR, Lankarani, MM, & Zamanian, H. (2016). Race by gender group differences in the protective effects of socioeconomic factors against sustained health problems across five domains. Journal of Racial and Ethnic Health Disparities. doi: 10.1007/s40615- 016-0291-3.

Assari, S., Smith, JR, Caldwell, CH, & Zimmerman, MA. (2015). Gender differences in longitudinal links between neighborhood fear, parental support, and depression among African American emerging adults. Societies, 5, 151-70. doi:10.3390/soc5010151.

Assari, S., Sonnega, A, Leggett, A, & Pepin, RL. (2016). Residual effects of restless sleep over depressive symptoms on chronic medical conditions: race by gender differences. Journal of Racial and Ethnic Health Disparities, 4, 59-69. doi: 10.1007/s40615-015-0202-z.

Assari, S., Thomas, A, Cadlwell, C, & Mincy, R. (2017). Blacks' Diminished Health Return of Family Structure and Socioeconomic Status; 15 Years of Follow-up of a National Urban Sample of Youth. Journal of Urban Health. 2017. In Press. doi: 10.1007/s11524-017-0217-3

Bailey, Z. D., Krieger, N., Agénor, M., Graves, J., Linos, N., & Bassett, M. T. (2017). Structural racism and health inequities in the USA: evidence and interventions. The Lancet, 389, 1453-1463.

Barnes L., L., de Leon CF, Lewis TT, Bienias, JL, Wilson, RS, & Evans, DA. (2008). Perceived discrimination and mortality in a population-based study of older adults. American Journal of Public Health, 98, 1241-7. doi: 10.2105/AJPH.2007.114397.

Bauer, G. R. (2014). Incorporating intersectionality theory into population health research methodology: challenges and the potential to advance health equity. Social Science & Medicine, 110, 10-17.

Bennett, G. G., Merritt, M. M., Sollers, III JJ, Edwards, CL, Whitfield, KE, Brandon, DT, & Tucker, RD. (2004). Stress, coping, and health outcomes among African-Americans: A review of the John Henryism hypothesis. Psychology & Health, 19, 369-83.

Bitler, M., & Hoynes, H. (2016). Strengthening Temporary Assistance for Needy Families. The Hamilton Project, Policy Proposal, 4.

Bocian, D. G., Ernst, K. S., & Li, W. (2008). Race, ethnicity and subprime home loan pricing. Journal of Economics and Business, 60, 110-124.

Bocian, D. G., Li, W., & Ernst, K. S. (2010). Foreclosures by Race and Ethnicity. Center for Responsible Lending, 4-6.

Bowen, M. E., & González, H. M. (2010). Childhood socioeconomic position and disability in later life: results of the health and retirement study. American journal of public health, 100, S197– 203.10.2105/AJPH.2009.160986

Bowleg, L., Huang, J., Brooks, K., Black, A., & Burkholder, G. (2003). Triple jeopardy and beyond: Multiple minority stress and resilience among Black lesbians. Journal of Lesbian Studies, 7, 87-108.

Brown, C.S., Baker, T.A., Mingo, C.A., Harden, J.T., Whitfield, K., Aiken-Morgan, A.T., Phillips, K.L. and Washington, T., (2014). A review of our roots: blacks in gerontology. Gerontologist, 54, 108-16. doi: 10.1093/geront/gnt103.

Brown, T. H., O’Rand, A. M., & Adkins, D. E. (2012). Race-ethnicity and health trajectories: tests of three hypotheses across multiple groups and health outcomes. Journal of Health and Social Behavior, 53, 359-77. doi: 10.1177/0022146512455333.

Caldwell, C. H., Antonakos, C. L., Tsuchiya, K., Assari, S., & De Loney, E. H. (2013). Masculinity as a moderator of discrimination and parenting on depressive symptoms and drinking behaviors among nonresident African-American fathers. Psychology of Men & Masculinity, 14,47.

Caprio, S., Daniels, S. R., Drewnowski, A., Kaufman, F. R., Palinkas, L. A., Rosenbloom, A. L., ... & Kirkman, M. S. (2008). Influence of race, ethnicity, and culture on childhood obesity: implications for prevention and treatment. Obesity, 16, 2566-2577.

Card, D., & Krueger, A. B. (1992). School quality and black-white relative earnings: A direct assessment. The Quarterly Journal of Economics, 107, 151-200.

Carter, JD, & Assari, S. (2017). Sustained Obesity and Depressive Symptoms over 6 Years: Race by Gender Differences in the Health and Retirement Study. Frontiers in Aging Neuroscience, 8, 312. doi: 10.3389/fnagi.2016.00312.

Case, A, & Deaton, A. (2015). Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century. Proceedings of the National Academy of Sciences, 112,15078-83. doi: 10.1073/pnas.1518393112.

Castro, K. G. (1993). Distribution of acquired imnlunodeficiency syndrome and other sexually transmitted diseases in racial and ethnic populations, United States: influences of life-style and socioeconomic status. Annals of Epidemiology, 3, 181-4.

Ceci, S. J., & Papierno, P. B. (2005). The rhetoric and reality of gap closing: when the "have-nots" gain but the "haves" gain even more. American Psychologist, 60, 149-60.

Chae, D. H., Nuru-Jeter, A. M., Adler, N. E., Brody, G. H., Lin, J., Blackburn, E. H., & Epel, E. S. (2014). Discrimination, racial bias, and telomere length in African-American men. American journal of preventive medicine, 46, 103-11. doi: 10.1016/j.amepre.2013.10.020.

Cheung, F. (2017). Income redistribution predicts greater life satisfaction across individual, national, and cultural Characteristics. Journal of Personality and Social Psychology. In Press. doi: 10.1037/pspp0000164.

Colen, C. G. (2011). Addressing racial disparities in health using life course perspectives: toward a constructive criticism. Du Bois Review: Social Science Research on Race, 8, 79-94. doi: 10.1017/S1742058X11000075

Collins, S. M. (1983). The making of the black middle class. Social Problems, 30, 369-382.

Collins, P. H. (2015). Intersectionality's definitional dilemmas. Annual Review of Sociology, 41, 1-20.

Conway, K. (1986). Coping with the stress of medical problems among black and white elderly. The International Journal of Aging and Human Development, 21, 39-48.

Crosby, F. J. (2004). Affirmative action is dead: Long live affirmative action. Yale University Press.

Cutler, D. M., & Lleras-Muney, A. (2006). Education and health: evaluating theories and evidence. National bureau of economic research. Available at: http://www.nber.org/papers/w12352

Dansby, I. (1996). Affirmative action, or reverse discrimination? Journal of Intergroup Relations, 24, 37-48.

Desilver, D. (2013). Black unemployment rate is consistently twice that of whites. Pew Research Center, 21.

DiAngelo, R. (2011). White fragility. The International Journal of Critical Pedagogy, 3.

Dowd, J. J., & Bengtson, V. L. (1978). Aging in minority populations an examination of the double jeopardy hypothesis. Journal of Gerontology, 33, 427-436.

Dressler, W. W. (1993). Health in the African-American community: accounting for health inequalities. Medical Anthropology Quarterly, 7, 325-345.

Ebaugh, H. R. & Curry, M. (2000). Fictive kin as social capital in new immigrant communities. Sociological Perspectives, 43, 189-209.

Everson-Rose, S. A., & Lewis, T. T. (2005). Psychosocial factors and cardiovascular diseases. Annual Review of Public Health, 26, 469-500. doi: 10.1146/annurev.publhealth.26.021304.144542

Everson-Rose, S. A., House, J. S., & Mero, R. P. (2004). Depressive symptoms and mortality risk in a national sample: confounding effects of health status. Psychosomatic Medicine, 66, 823-30.

Farmer, M. M., & Ferraro, K. F. (2005). Are racial disparities in health conditional on socioeconomic status? Social Science & Medicine, 60, 191-204.

Fedewa, S. A., McClellan, W. M., Judd, S., Gutiérrez, O. M., & Crews, D. C. (2014). The association between race and income on risk of mortality in patients with moderate chronic kidney disease. BMC nephrology, 15, 136.

Feldman, J. J., Makuc, D. M., Kleinman, J. C., & Cornoni- Huntley, J. (1989). National trends in educational differentials in mortality. American Journal of Epidemiology, 129, 19-33.

Fenning, P., & Rose, J. (2007). Overrepresentation of African American students in exclusionary discipline the role of school policy. Urban Education, 42, 536-559.

Fewell, Z., Davey Smith, G., & Sterne, J. A. (2007). The impact of residual and unmeasured confounding in epidemiologic studies: a simulation study. American journal of epidemiology, 166, 646-655.

Freeman, H. P. (1993). Poverty, race, racism, and survival. Annals of Epidemiology, 3, 145-49.

Fuller-Rowell, T. E., & Doan, S. N. (2010). The social costs of academic success across ethnic groups. Child Development, 81, 1696-713. doi: 10.1111/j.1467-8624.2010.01504.x.

Fuller-Rowell, T. E., Curtis, D. S., Doan, S. N., & Coe, C. L. (2015). Racial disparities in the health benefits of educational attainment: a study of inflammatory trajectories among African American and white adults. Psychosomatic Medicine, 77, 33-40. doi: 10.1097/PSY.0000000000000128.

Gee, G. C. & Ford, C. L. (2011). Structural racism and health inequities: Old Issues, New Directions. Du Bois Review, 8, 115-132.

Geronimus, AT, James, SA, Destin, M, Graham, LA, Hatzenbuehler, M, Murphy, M, Pearson, JA, Omari, A, & Thompson, JP. (2016). Jedi public health: Co-creating an identity-safe culture to promote health equity. SSM-population health, 2, 105-116. doi: 10.1016/j.ssmph.2016.02.008

Geronimus, A. T., Pearson, J. A., Linnenbringer, E., Schulz, A. J., Reyes, A. G., Epel, E. S., ... & Blackburn, E. H. (2015). Race-ethnicity, poverty, urban stressors, and telomere length in a Detroit community-based sample. Journal of health and social behavior, 56, 199-224. doi: 10.1177/0022146515582100.

Graham, H., & Kelly, M. Health Inequalities: Concepts, Frameworks and Policy. London: Health Development Agency, 2004.

Griffith, K, Evans, L, Bor, J. (2017). The affordable care act reduced socioeconomic disparities in health care access. Health Affairs, In Press. doi: 10.1377/hlthaff.2017.0083

Grogger, J. (1996) Does school quality explain the recent black/white wage trend? Journal of Labor Economics, 14, 231–53.10.1086/209810.

Grollman, E. A. (2014). Multiple disadvantaged statuses and health: the role of multiple forms of discrimination. Journal of health and social behavior, 55, 3-19.

Gueorguieva, R, Sindelar, JL, Falba, TA, Fletcher, JM, Keenan, P, Wu, R, & Gallo, WT. (2009). The impact of occupation on self-rated health: cross-sectional and longitudinal evidence from the health and retirement survey. The journals of gerontology. Series B, Psychological sciences and social sciences. 64, 118-24. doi: 10.1093/geronb/gbn006.

Hamilton, C. V., & Ture, K. (2011). Black power: Politics of liberation in America. Vintage.

Hancock, A. M. (2007). When multiplication doesn't equal quick addition: Examining intersectionality as a research paradigm. Perspectives on politics, 5, 63-79.

Hanushek, E. A., & Wößmann, L. (2007). The role of education quality for economic growth. [accessed November 2017]. Available from: https://elibrary.worldbank.org/doi/abs/10.1596/1813- 9450-4122

Herd, P., Goesling, B., & House, J. S. (2007) Socioeconomic position and health: the differential effects of education versus income on the onset versus progression of health problems. Journal of Health and Social Behavior 48, 223–38. doi: 10.1177/002214650704800302.

Herrnstein, R. J., & Murray, C. (2010). Bell curve: intelligence and class structure in American life. Simon and Schuster. pp. 22–23.

Hickson, DA, Lewis, TT, Liu, J, Mount, DL, Younge, SN, Jenkins, WC, Sarpong, DF, & Williams, DR. (2012). The associations of multiple dimensions of discrimination and abdominal fat in African American adults: the Jackson Heart Study. Annals of Behavioral Medicine. 43, 4-14. doi: 10.1007/s12160-011-9334-5.

Holmes, CJ, & Zajacova, A (2014). Education as “the great equalizer”: health benefits for black and white adults. Social Science Quarterly, 95, 1064-85.

Hope, M. O., Assari, S., Cole-Lewis, Y. C., & Caldwell, C. H. (2017). Religious social support, discrimination, and psychiatric disorders among Black adolescents. Race and Social Problems, 9, 102- 114.

Hudson, D. L., Bullard, K. M., Neighbors, H. W., Geronimus, A. T., Yang, J., & Jackson, J. S. (2012). Are benefits conferred with greater socioeconomic position undermined by racial discrimination among African American men? Journal of Mens’ Health, 9, 127-136.

Hudson, D. L., Neighbors, H. W., Geronimus, A. T., & Jackson, J. S. (2016). Racial discrimination, John Henryism, and depression among African Americans. Journal of Black Psychology, 42, 221-243.

Huffman, M. L., & Cohen, P. N. (2004). Racial wage inequality: job segregation and devaluation across US labor markets. American Journal of Sociology, 109, 902–36.

Hummer, R. A., Ellison, C. G., Rogers, R. G., Moulton, B. E., & Romero, R. R. (2004). Religious involvement and adult mortality in the United States: review and perspective. The Southern Medical Journal, 97, 1223-30.

Hummer, R. A., Rogers, R. G., Nam, C. B., & Ellison, C. G. (1999). Religious involvement and U.S. adult mortality. Demography, 36, 273-85.

IWPR. Importance of Social Security by Gender, Race/Ethnicity, and Marital Status. The Institute for Women’s Policy Research (IWPR) (2010). [accessed July 2017]. Available from: http://www.iwpr.org/publications/pubs/importance-of-social-security-by-gender-race-ethnicity- and-marital-status-2010

Jackson, J. S., Govia, I. O., Sellers, S. L. (2010). Race and ethnic influences over the life-course. In Binstock R. H., George L. K. (Eds.), Handbook of aging and the social sciences (7th ed., pp. 91-103). New York, NY: Academic Press.

Jackson, J. S., Knight, K. M., & Rafferty, J. A. (2010). Race and unhealthy behaviors: chronic stress, the HPA axis, and physical and mental health disparities over the life course. American Journal of Public Health, 100, 933-9. doi: 10.2105/AJPH.2008.143446.

James, S. A., Strogatz, D. S., Wing, S. B., & Ramsey, D. L. (1987). Socioeconomic status, John Henryism, and hypertension in blacks and whites. American Journal of Epidemiology, 126, 664-73.

James, S. A. (1994). John Henryism and the health of African-Americans. Culture, medicine and psychiatry, 18, 163-82.

Jencks, C., & Mayer, S. E. (1990). Residential segregation, job proximity, and black job opportunities. Inner-City Poverty in the United States, 187–222. https://www.nap.edu/read/1539/chapter/7

Jencks, C., & Phillips, M. (Eds.) (2011). The Black-White test score gap. Brookings Institution Press.

Katz, P. A., & Taylor, D. A. (Eds.). (2013). Eliminating racism: Profiles in controversy. Springer Science & Business Media.

Kaufman, JS, Cooper, RS, & McGee, DL. (1997). Socioeconomic status and health in blacks and whites: the problem of residual confounding and the resiliency of race. Epidemiology, 8, 621-8.

Kennedy, B. R., Mathis, C. C., & Woods, A. K. (2007). African Americans and their distrust of the health care system: healthcare for diverse populations. Journal of cultural diversity, 14, 56.

Kessler, R. C., & Neighbors, H. W. (1986). A new perspective on the relationships among race, social class, and psychological distress. Journal of Health and Social Behavior, 27, 107–115.

Keyes, C. L. (2009). The Black-White paradox in health: flourishing in the face of social inequality and discrimination. Journal of Personality, 77, 1677-706. doi: 10.1111/j.1467-6494.2009.00597.x.

King, D. K. (1988). Multiple jeopardy, multiple consciousness: The context of a Black feminist ideology. Signs: Journal of Women in Culture and Society, 14, 42-72.

Kitayama, S., & Park, J. (2010). Cultural neuroscience of the self: understanding the social grounding of the brain. Social cognitive and affective neuroscience, 5, 111-129.

Kochanek, K. D., Maurer, J. D., & Rosenberg, H. M. (1994). Why did black life expectancy decline from 1984 through 1989 in the United States? American Journal of Public Health, 84, 938-44.

Krause, N. (2002). Church-based social support and health in old age: exploring variations by race. Journals of Gerontology, Series B: Psychological Sciences and Social Sciences, 57, S332–47.

Krieger, N. (2012). Methods for the scientific study of discrimination and health: an ecosocial approach. American Journal of Public Health, 102, 936-44. doi: 10.2105/AJPH.2011.300544.

Lankarani, M. M., & Assari, S. (2017). Positive and negative affect more concurrent among blacks than whites. Behavioral Sciences, 7, pii: E48. doi: 10.3390/bs7030048.

Lantz, P. M., House, J. S., Mero, R. P., & Williams, D. R. (2005). Stress, life events, and socioeconomic disparities in health: Results from the Americans' Changing Lives Study. Journal of health and social behavior, 46, 274-288.

LaVeist, T., Pollack, K., Thorpe, R., Fesahazion, R., Gaskin, D. (2011). Place, not race: Disparities dissipate in southwest Baltimore when Blacks and Whites live under similar conditions. Health Affairs, 30, 1880-1887. doi:10.1377/hlthaff.2011.0640

LaVeist, T. A. (2005). Disentangling race and socioeconomic status: a key to understanding health inequalities. Journal of Urban Health, 82, iii, 26–34.

LaVeist, T. A., Thorpe, R. J., Pierre, G., Mance, G. A., & Williams, D. R. (2014). The relationships among vigilant coping style, race, and depression. Journal of Social Issues, 70, 241-255. doi: 10.1111/josi.12058

LaVeist, T.A., (2005). Disentangling race and socioeconomic status: a key to understanding health inequalities. Journal of Urban Health, 82, pp.iii26-iii34. doi: 10.1093/jurban/jti061.

Lee, D. B., Peckins, M. K., Heinze, J. E., Miller, A. L., Assari, S., & Zimmerman, M. A. (2017). Psychological pathways from racial discrimination to cortisol in African American males and females. Journal of Behavioral Medicine, 1-13. doi: 10.1007/s10865-017-9887-2.

Leonard, J. S. (1990). The impact of affirmative action regulation and equal employment law on black employment. The Journal of Economic Perspectives, 4, 47-63.

Leopold, L., & Engelhartdt, H. (2013). Education and physical health trajectories in old age. Evidence from the Survey of Health, Ageing and Retirement in Europe (SHARE). International journal of public health, 58, 23-31. doi: 10.1007/s00038-012-0399-0

Lewis, T. T., Williams, D. R., Tamene, M., & Clark, C. R. (2014). Self-reported experiences of discrimination and cardiovascular disease. Current Cardiovascular Risk Reports, 8,365. doi: 10.1007/s12170-013-0365-2.

Lewis, C. W., James, M., Hancock, S., & Hill-Jackson, V. (2008). Framing African American students' success and failure in urban settings: A typology for change. Urban Education, 43, 127-153.

Lincoln, K. D., Chatters, L. M., & Taylor, R. J. (2003). Psychological distress among Black and White Americans: differential effects of social support, negative interaction and personal control. Journal of Health and Social Behavior, 44, 390–407.

Link, B, & Phelan, J. (1995). Social conditions as fundamental causes of disease. Journal of Health and Social Behavior, 36, 80–94. Doi: 10.2307/2626958.

Lorenc, T., Petticrew, M., Welch, V., & Tugwell, P. (2013). What types of interventions generate inequalities? Evidence from systematic reviews. Journal of Epidemiology and Community Health, 67, 190-193. doi: 10.1136/jech-2012-201257.

Lu, M. C., & Halfon, N. (2003). Racial and ethnic disparities in birth outcomes: a life-course perspective. Maternal and child health journal, 7, 13-30.

Lyons, D. M., Parker, K. J., Katz, M., & Schatzberg, A. F. (2009). Developmental cascades linking stress inoculation, arousal regulation, and resilience. Frontiers in Behavioral Neuroscience, 3. doi: 10.3389/neuro.08.032.2009.

MacDorman, M. F. (2011). Race and ethnic disparities in fetal mortality, preterm birth, and infant mortality in the United States: an overview. Seminars in Perinatology, 35, 200-8. doi: 10.1053/j.semperi.2011.02.017.

Malat, J., Mayorga-Gallo, S., & Williams, D. R. (2017). The effects of whiteness on the health of whites in the USA. Social Science & Medicine, In Press. doi.org/10.1016/j.socscimed.2017.06.034.

Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological review, 98, 224.

Marmot, M. (2015). The health gap: the challenge of an unequal world. Bloomsbury Publishing.

Marmot, M., Allen, J., Bell, R., & Goldblatt, P. (2012). Building of the global movement for health equity: from Santiago to Rio and beyond. The Lancet, 379, 181-188. doi: 10.1016/S0140- 6736(11)61506-7.

Mays, V. M., Cochran, S. D., & Barnes, N. W. (2007). Race, race-based discrimination, and health outcomes among African Americans. Annual Review of Psychology, 58, 201-25.

McClellan, W., Warnock, D. G., McClure, L., Campbell, R. C., Newsome, B. B., Howard, V., ... & Howard, G. (2006). Racial differences in the prevalence of chronic kidney disease among participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) Cohort Study. Journal of the American Society of Nephrology, 17, 1710-1715.

McDonough, P., Williams, D. R., House, J. S., & Duncan, G. J. (1999). Gender and the socioeconomic gradient in mortality. Journal of Health and Social Behavior, 40, 17–31. Doi:10.2307/2676376.

McKinnon, J. (2003). The black population in the United States: March 2002. US Census Bureau, Current Population Reports, Series P20-541, Washington, DC.

Mehta, N., & Preston, S. (2016). Are major behavioral and sociodemographic risk factors for mortality additive or multiplicative in their effects? Social Science & Medicine, 154, 93-9. doi: 10.1016/j.socscimed.2016.02.009.

Mezuk, B., Kershaw, K. N., Hudson, D., Lim, K. A., & Ratliff, S. (2011). Job strain, workplace discrimination, and hypertension among older workers: The Health and Retirement Study. Race and Social Problems, 3, 38-50.

Miller, B., & Taylor, J. (2012). Racial and socioeconomic status differences in depressive symptoms among black and white youth: An examination of the mediating effects of family structure, stress and support. Journal of youth and adolescence, 41, 426-437.

Miller, J. E. (2000). The effects of race/ethnicity and income on early childhood asthma prevalence and health care use. American journal of public health, 90, 428–430.

Mirowsky, J., & Ross, C. E. (2003). Education, Social Status, and Health. New York: Aldine de Gruyter.

Mirowsky, J., & Ross, C. E. (2007). Life course trajectories of perceived control and their relationship to education. American Journal of Sociology, 112, 1339–1382.

Moazen-Zadeh, E., Assari, S. (2016). Depressive symptoms predict major depressive disorder after 15 years among whites but not blacks. Frontiers in Public Health, 4, 1-10. doi: 10.3389/fpubh.2016.00013.

Monnat, S. M. (2014). Race/ethnicity and the socioeconomic status gradient in women’s cancer screening utilization: a case of diminishing returns? Journal of Health Care for the Poor and Underserved, 25, 332–56. doi: 10.1353/hpu.2014.0050.

Morgenstern, L. B., Escobar, J. D., Sánchez, B. N., Hughes, R., Zuniga, B. G., Garcia, N., & Lisabeth, L. D. (2009) Fast food and neighborhood stroke risk. Annals of neurology, 66, 165-70. doi: 10.1002/ana.21726.

Mujahid, M. S., James, S. A., Kaplan, G. A., & Salonen, J. T. (2017). Socioeconomic position, John Henryism, and incidence of acute myocardial infarction in Finnish men. Social Science & Medicine, 173, 54-62.

Murray, C. J., Kulkarni, S. C., Michaud, C., Tomijima, N., Bulzacchelli, M. T., Iandiorio, T. J., & Ezzati, M. (2006). Eight Americas: investigating mortality disparities across races, counties, and race- counties in the United States. PLoS medicine, 3, e260.

National Center for Health Statistics. (1994a). Health United States 1993. Hyattsville, MD: USDHHS.

Navarro, V. (1990). Race or class versus race and class: mortality differentials in the United States. The Lancet, 336, 1238-1240.

Neighbors, H. W., Sellers, S. L., Zhang, R., & Jackson, J. S. (2011). Goal-striving stress and racial differences in mental health. Race and Social Problems, 3, 51-62.

Nelson, A. R., Stith, A. Y., & Smedley, B. D. (Eds.). (2002). Unequal treatment: confronting racial and ethnic disparities in health care (full printed version). National Academies Press.

Noguera, P. A. (2009). The trouble with black boys: And other reflections on race, equity, and the future of public education. John Wiley & Sons.

Oliver, M. L., & Shapiro, T. M. (2006). Black wealth, white wealth: A new perspective on racial inequality. Taylor & Francis.

O'Campo, P., & Rojas-Smith, L. (1998). Welfare reform and women's health: review of the literature and implications for state policy. Journal of Public Health Policy, 19, 420-446.

Pager, D., & Shepherd, H. (2008). The sociology of discrimination: Racial discrimination in employment, housing, credit, and consumer markets. Annual Review of Sociology, 34, 181-209.

Pappas, G., Queen, S., Hadden, W., & Fisher, G. (1993). The increasing disparity in mortality between socioeconomic groups in the United States, 1960 and 1986. New England journal of medicine, 329, 103-109.

Peterson, R. S. (1994). The role of values in predicting fairness judgments and support of affirmative action. Journal of Social Issues, 50, 95-115.

Phelan, J. C., Link, B. G., & Tehranifar, P. (2010). Social conditions as fundamental causes of health inequalities: theory, evidence, and policy implications. Journal of health and social behavior, 51, S28- S40. doi:10.1177/0022146510383498

Pope, M., Corona, R., & Belgrave, F. Z. (2014). Nobody's perfect: a qualitative examination of African American maternal caregivers' and their adolescent girls' perceptions of body image. Body Image, 11, 307-17. doi: 10.1016/j.bodyim.2014.04.005.

Rabinowitz, J. L., Sears, D. O., Sidanius, J., & Krosnick, J. A. (2009). Why do white Americans oppose race‐targeted policies? Clarifying the impact of symbolic racism. Political psychology, 30, 805-828.

Reskin, B. (2012) The Race Discrimination System. Annual Review of Sociology, 38, 17-35. doi: 10.1146/annurev-soc-071811-145508.

Roscigno, V. J., & Ainsworth-Darnell, J. W. (1999). Race, cultural capital, and educational resources: Persistent inequalities and achievement returns. Sociology of education, 72, 158-178.

Ross, S. L., & Yinger, J. (2002). The color of credit: Mortgage discrimination, research methodology, and fair-lending enforcement. MIT Press Books, 1.

Rowley, D. L., Hogue, C. J., Blackmore, C. A., Ferre, C. D., Hatfield-Timajchy, K., Branch, P., & Atrash, H. K. (1993). Preterm delivery among African-American women: a research strategy. American Journal of Preventive Medicine, 9, 1-6.

Rumberger, R. W. (1983). Dropping out of high school: The influence of race, sex, and family background. American Educational Research Journal, 20, 199-220.

Ryff, C. D., Keyes, C. L., & Hughes, D. L. (2003). Status inequalities, perceived discrimination, and eudaimonic well-being: Do the challenges of minority life hone purpose and growth?. Journal of health and Social Behavior, 44, 275-291.

Seaton, E. K., & Douglass, S. (2014). School diversity and racial discrimination among African- American adolescents. Cultural Diversity and Ethnic Minority Psychology, 20, 156-65. doi: 10.1037/a0035322.

Sellers, S. L., & Neighbors, H. W. (1999). Goal‐striving stress, social economic status, and the mental health of black Americans. Annals of the New York Academy of Sciences, 896, 469-473.

Sellers, S. L., & Neighbors, H. W. (2008). Effects of goal-striving stress on the mental health of Black Americans. Journal of Health and Social Behavior, 49, 92-103.

Shapiro, T. M. (2006). Race, homeownership and wealth. Washington University Journal of Law & Policy, 20, 53.

Shaywitz, B. A., Shaywitz, S. E., Pugh, K. R., & Constable, R. T. (1995). Sex differences in the functional organization of the brain for language. Nature, 373, 607.

Steele, C. M. (1992). Race and the schooling of Black Americans. The Atlantic Monthly, 269, 68-78.

Taylor, R. J., & Chatters, L. M. (1991). Extended family networks of older black adults. Journal of Gerontology, 46, S210-S217.

Thomas, A., Caldwell, C. H., Assari, S., Jagers, R. J., & Flay, B. (2016). You do what you see: how witnessing physical violence is linked to violent behavior among male African American adolescents. The Journal of Men’s Studies, 24, 185-207.

Turiano, N. A., Chapman, B. P., Agrigoroaei, S., Infurna, F. J., & Lachman, M. (2014). Perceived control reduces mortality risk at low, not high, education levels. Health Psychology, 33, 883-90. doi: 10.1037/hea0000022.

U.S. Department of Labor, Bureau of Labor Statistics, The Economics Daily, Occupational employment by race and ethnicity, 2011 on the Internet at https://www.bls.gov/opub/ted/2012/ted_20121026.htm (visited July 22, 2017).

Wagener, D. K., & Schatzkin, A. (1994). Temporal trends in the socioeconomic gradient for breast cancer mortality among U.S. women. American Journal of Public Health, 84, 1003-06.

Wald, J., & Losen, D. J. (2003). Defining and redirecting a school‐to‐prison pipeline. New Directions for Student Leadership, 99, 9-15.

Warner, D. F., & Hayward, M. D. (2006). Early-life origins of the race gap in men's mortality. Journal of Health and Social Behavior, 47, 209-26.

White, A. M., (2009). Borrowing while black: applying fair lending laws to risk-based mortgage pricing. South Carolina Law Review, 60, Available at SSRN: https://ssrn.com/abstract=1507289

Whitehead, M., Dahlgren, G. (2006). Concepts and principles for tackling social inequities in health: levelling up part 1. Copenhagen: WHO Regional Office for Europe.

WHO Commission on Social Determinants of Health, & World Health Organization. (2008). Closing the gap in a generation: health equity through action on the social determinants of health: Commission on Social Determinants of Health final report. World Health Organization.

Wilhelm, M. (1987). Controversy: In America’s pastime, says Frank Robinson, White is the color of the game off the field. People, 46.

Williams, D. R. (2012). Miles to go before we sleep: Racial inequities in health, Journal of health and social behavior, 53, 279-95.

Williams, D. R., & Collins, C. (1995). U.S. socioeconomic and racial differences in health: patterns and explanations. Annual Review of Sociology, 21, 349–386.

Williams, D. R., & Mohammed, S. A. (2013). Racism and health I: Pathways and scientific evidence. American Behavioral Scientist, 57, 1152-1173. doi: 10.1177/0002764213487340.

Williams, D. R., & Mohammed, S. A. (2013). Racism and health II: a needed research agenda for effective interventions. American Behavioral Scientist, 57, 1200–1226. doi: 10.1177/0002764213487341.

Williams, D. R., & Purdie-Vaughns, V. (2016). Needed Interventions to Reduce Racial/Ethnic Disparities in Health. Journal of Health Politics, Policy and Law, 41, 627-51. doi: 10.1215/03616878- 3620857.

Williams, D. R., Neighbors, H. W., & Jackson, J. S. (2003). Racial/ethnic discrimination and health: findings from community studies. American journal of public health. 93, 200-8.

Williams, D. R., Priest, N., & Anderson, N. B., (2016). Understanding associations among race, socioeconomic status, and health: Patterns and prospects. Health Psychology, 35, 407-11. doi: 10.1037/hea0000242.

Williams, D. R., Mohammed, S. A., Leavell, J., & Collins, C. (2010). Race, socioeconomic status, and health: complexities, ongoing challenges, and research opportunities. Annals of the New York Academy of Sciences, 1186, 69-101. doi: 10.1111/j.1749-6632.2009.05339.x.

Zimmerman, M. A., Ramirez-Valles, J., & Maton, K. I. (1999). Resilience among urban African American male adolescents: A study of the protective effects of sociopolitical control on their mental health. American journal of community psychology, 27, 733-751.

Table 1. Differential effects of psychosocial factors on health of Blacks than Whites

Data Panel Follow Up Author

set Predictor Outcome

ACL + 25 Years Assari & Lankarani,

Education Mortality 2016a

ACL + 25 Years Employment Mortality Assari, 2017a

ACL + 25 Years Neighborhood Safety Mortality Assari, 2016a

ACL + 25 Years Social Contacts Mortality Assari, 2017b

ACL + 25 Years Assari, Lankarani, &

Self-Rated Health Mortality Burgard, 2015

ACL + 25 Years Assari, Moazen-Zadeh,

Lankarani, & Micol-

Depression Mortality Foster, 2016

ACL + 25 Years Anger & Hostility Mortality Assari, 2016b

ACL + 25 Years Self-Efficacy Mortality Assari, 2016c

RAHS + 3 Years Sense of Control Mortality Assari, 2017d

ACL + 25 Years Depression Mortality Assari & Burgard, 2015

NSAL - - Depression Obesity Assari, 2014

FFWS + 15 Years Family Assari, Thomas,

Socioeconomic Caldwell, & Mincy, 2017

Status Obesity

ACL + 25 Years Chronic Assari, Burgard, & Zivin,

Depression Disease 2015

ACL + 25 Years Chronic Assari, Sonnega,

Restless Sleep Disease Leggett, & Pepin, 2017

FFCWS + 15 Years Family Assari. Caldwell, &

Socioeconomic Self-Rated Mincey, 2017

Status Health

HRS + 6 Years Sleep, Assari, Nikahd,

Body Mass Malekahmadi,

Index , Lankarani, & Zamanian,

Education Exercise 2016

RAHS - - Body Mass Assari, 2016c

Life Purpose Index

NSAL - - Suicidal Assari, 2015

Education Ideation

RAHS - - Assari & Lankarani,

Education Alcohol Use 2016d

NSAL - - Assari & Lankarani,

Stress Depression 2016c

NSAL - - Income Depression Assari & Caldwell 2017e

ACL + 25 Years Education Depression Assari, 2017b

ACL + 15 Years Depressive Moazen-Zadeh & Assari,

Symptoms Depression 2016

ACL + 25 Years Neuroticism Depression Assari, 2017f

NSAL - - Intention Assari & Lankarani,

to reduce 2015

Obesity weight

ACL, Americans’ Changing Lives; HRS, Health and Retirement Study; RAHS, Religion, Aging, and Health Survey; FFCWS, Fragile Families and Child Wellbeing Study; NSAL, National Survey of American Life

Author Bio

Shervin Assari’s health services research centers around community mental health settings, spanning issues of suicide, violence, drug use, and other high-risk behaviors, as well as the comorbidity of chronic mental health and medical conditions. He also focuses on studying health disparities due to race, gender, and socioeconomic status. Dr. Assari received his M.D. in Primary Health Care from Shahrekord University, and an M.P.H. in Health Behavior and Health Education from the University of Michigan.